Who Shapes What We Learn? Technology and Our Personal Learning Networks
This week’s discussion made me think about how technology influences what we learn through our Personal Learning Networks (PLNs). Before this, I mostly viewed platforms like LinkedIn as tools for discovering information, connecting with professionals, and keeping up with developments in my field. However, through my research experience in Health Information Science, I have realized that technology does not simply provide information. It also influences which ideas we encounter, whose perspectives we hear, and what we might overlook.
As a research assistant, I explore topics such as clinical information systems, artificial intelligence, and machine learning. My research experience has shown me that understanding these topics requires looking beyond technical developments. For example, when exploring AI in healthcare, it is important to consider not only how the technology works but also how it affects patients, healthcare professionals, privacy, and clinical workflows.LinkedIn helps me discover research, follow professionals, and learn about developments beyond my university courses. Boyd and Ellison (2007) explain how social networking sites enable people to establish connections and explore their networks. These connections can make learning more accessible and create opportunities to engage with people whose expertise differs from our own.
Although technology helps us discover relevant information, recommendations can also limit our exposure to different perspectives. If I frequently interact with posts about AI in healthcare, LinkedIn may continue recommending similar content. While this can help me stay informed, it might also mean that I encounter fewer discussions about the limitations of AI, patient experiences, or privacy concerns.Noble (2018), in Algorithms of Oppression, examines how search engines can reinforce existing social inequalities. Her work reminds us that digital platforms are not necessarily neutral in how they organize and present information.
This is important when building a PLN because seeing similar ideas repeatedly does not necessarily mean we are getting a complete understanding of a subject.My research experience has taught me the value of considering different perspectives before drawing conclusions. I can apply this lesson to my PLN by following not only AI researchers but also clinicians, healthcare professionals, and privacy experts. I can also search for original research and explore viewpoints that challenge my existing understanding instead of relying entirely on recommended content.
Technology makes it easier to connect and learn, but we still need to make conscious decisions about the information we consume. A meaningful PLN is not just about what technology brings to our attention, but also about what we actively choose to explore beyond it.
References
Boyd, D. M., & Ellison, N. B. (2007). Social network sites: Definition, history, and scholarship. Journal of Computer-Mediated Communication, 13(1), 210–230. https://doi.org/10.1111/j.1083-6101.2007.00393.x
Noble, S. U. (2018). Algorithms of oppression: How search engines reinforce racism. New York University Press.